Theta-alpha Band Research Articles

Pallidal Recordings in Chronically Implanted Dystonic Patients: Mitigation of Tremor-Related Artifacts.

Low-frequency oscillatory patterns of pallidal local field potentials (LFPs) have been proposed as a physiomarker for dystonia and hold the promise for personalized adaptive deep brain stimulation. Head tremor, a low-frequency involuntary rhythmic movement typical of cervical dystonia, may cause movement artifacts in LFP signals, compromising the reliability of low-frequency oscillations as biomarkers for adaptive neurostimulation. We investigated chronic pallidal LFPs with the PerceptTM PC (Medtronic PLC) device in eight subjects with dystonia (five with head tremors). We applied a multiple regression approach to pallidal LFPs in patients with head tremors using kinematic information measured with an inertial measurement unit (IMU) and an electromyographic signal (EMG). With IMU regression, we found tremor contamination in all subjects, whereas EMG regression identified it in only three out of five. IMU regression was also superior to EMG regression in removing tremor-related artifacts and resulted in a significant power reduction, especially in the theta-alpha band. Pallido-muscular coherence was affected by a head tremor and disappeared after IMU regression. Our results show that the Percept PC can record low-frequency oscillations but also reveal spectral contamination due to movement artifacts. IMU regression can identify such artifact contamination and be a suitable tool for its removal.

A Routine Electroencephalography Monitoring System for Automated Sports-Related Concussion Detection.

Cases of concussions in the United States keep increasing and are now up to 2 million to 3 million incidents per year. Although concussions are recoverable and usually not life-threatening, the degree and rate of recovery may vary depending on age, severity of the injury, and past concussion history. A subsequent concussion before full recovery may lead to more-severe brain damage and poorer outcomes. Electroencephalography (EEG) recordings can identify brain dysfunctionality and abnormalities, such as after a concussion. Routine EEG monitoring can be a convenient method for reducing unreported injuries and preventing long-term damage, especially among groups with a greater risk of experiencing a concussion, such as athletes participating in contact sports. Because of the relative availability of EEG compared to other brain-imaging techniques (e.g., functional magnetic resonance imaging), the use of EEG monitoring is growing for various neurological disorders. In this longitudinal study, EEG was analyzed from 4 football athletes before their athletic season and also within 7 days of concussion. Compared to a control group of 4 additional athletes, a concussion was detected with up to 99.5% accuracy using EEG recordings in the Theta-Alpha band. Classifiers that use data from only a subset of the EEG electrodes providing reliable detection are also proposed. The most effective classifiers used EEG recordings from the Central scalp region in the Beta band and over the Temporal scalp region using the Theta-Alpha band. This proof-of-concept study and preliminary findings suggest that EEG monitoring may be used to identify a sports-related concussion occurrence with a high level of accuracy and thus reduce the chance of unreported concussion.

Electroencephalographic cross-frequency coupling and multiplex brain network under manual acupuncture stimulation

Increasing evidence indicates that acupuncture can modulate neural system dynamic and brain activity. Except for within-frequency coupling (WFC), cross-frequency coupling (CFC) also plays a crucial role in the process of information transfer and integration within brain areas. In this paper, with the cross-frequency phase synchronization technique, CFC under acupuncture is investigated using multi-channel EEG signals during acupuncture at “Zusanli” acupoint. The results show that the CFC under acupuncture significantly increases in delta-theta, delta-alpha, and theta-alpha bands. Brain functional networks including WFC networks and multiplex CFC networks are further reconstructed. The evolution of WFC network structure under acupuncture is explored by graph metrics, and it is found that the value of small world index significantly declines in delta and theta bands while increases in alpha and beta bands in acupuncture state. The ability of functional integration and segregation of the cross-frequency networks are further quantified via multiplex network features. In CFC network, the increments of multiplex clustering coefficient (MCC) and multiplex participation coefficient (MPC) in alpha and beta bands indicate that acupuncture could promote information integration and segregation across high rhythms. In addition, post-effect of acupuncture is obvious in alpha and beta bands, which can infer that alpha and beta rhythms play an essential part in the modulation of brain function by acupuncture. Besides, the change of matrix eigenvalue indicates that acupuncture impacts on brain dynamics by changing brain structure. These results provide a novel perspective to explore the alteration of brain function under manual acupuncture stimulation.

Cortical activity during sensorial tactile stimulation in healthy adults through Vojta therapy. A randomized pilot controlled trial

BackgroundBrain’s is stimulated by Vojta Therapy through selected body areas activating stored innate motor programs which are exported as coordinate movement and muscle contractions to trunk and limbs. The aim of this pilot study is to know the responses at cortical level to a specific tactile input, assessed by electroencephalography (EEG), compared to a sham stimulation, in healthy subjects.MethodsA randomized-controlled trial was conducted. Participants were randomly distributed into two groups: a non-specific tactile input-group (non-STI-group) (n = 20) and a Vojta specific tactile input-group (V-STI-group) (n = 20). The non-STI-group was stimulated in a non specific area (quadriceps distal area) and V-STI-group was stimulated in a specific area (intercostal space, at the mammillary line between the 7th and 8th ribs) according to the Vojta therapy. Recording was performed with EEG for 10 min considering a first minute of rest, 8 min during the stimulus and 1 min after the stimulus. EEG activity was recorded from 32 positions with active Ag/AgCl scalp electrodes following the 10–20 system. The continuous EEG signal was split into consecutive segments of one minute.ResultsThe V-STI-group showed statistically significant differences in the theta, low alpha and high alpha bands, bilaterally in the supplementary motor (SMA) and premotor (PMA) areas (BA6 and BA8), superior parietal cortex (BA5, BA7) and the posterior cingulate cortex (BA23, BA31). For the V-STI-group, all frequency bands presented an initial bilateral activation of the superior and medial SMA (BA6) during the first minute. This activation was maintained until the fourth minute. During the fourth minute, the activation decreased in the three frequency bands. From the fifth minute, the activation in the superior and medial SMA rose again in the three frequency bandsConclusionsOur findings highlight that the specific stimulation area at intercostal space, on the mammillary line between 7 and 8th ribs according to Vojta therapy differentially increased bilateral activation in SMA (BA6) and Pre-SMA (BA8), BA5, BA7, BA23 and BA31 in the theta, low and high alpha bands in healthy subjects. These results could indicate the activation of innate locomotor circuits during stimulation of the pectoral area according to the Vojta therapy.Trial registration Retrospectively registered. This randomized controlled trial has been registered at ClinicalTrials.gov Identifier: NCT04317950 (March 23, 2020).

Diabetic patients are deficient in intentional visuospatial learning and show different learning-related patterns of theta and gamma EEG activity

ABSTRACT Introduction: We hypothesized that diabetic patients without mild cognitive impairment would present deficiencies in visuospatial incidental/intentional memory processing and alterations in the underlying EEG alpha, theta and gamma patterns. Methods: Non-diabetic, diabetic-controlled, and diabetic-uncontrolled patients underwent a visuospatial incidental-intentional memory test under simultaneous recording of temporal, parietal, and frontal EEG. The test required patients to solve a maze, with eight objects irrelevant to the task, embedded in it, after an interference instruction, participants were asked to recall the positions of the objects (incidental test). Finally, the participants were explicitly told to study the object positions, and then were asked to recall the objects again (intentional test). Power from baseline, incidental learning, incidental memory, and intentional learning conditions was obtained in alpha, theta, and low-gamma bands. Comparisons were made across groups and conditions for each band, with age, sex, and years from the diagnosis as covariates (ANCOVA with blocking). Results: Diabetic patients showed spared incidental but deficient intentional visuospatial learning. Uncontrolled patients showed a more profound intentional learning deficit as they scored similar numbers of correct positions under incidental and intentional conditions; whereas, non-diabetic and diabetic-controlled patients increased their number after the intentional study. Non-diabetic participants showed increased power during intentional learning compared with the baseline condition in frontal theta, frontoparietal gamma (Fp2 and P4) and frontal alpha (F4) bands; whereas in diabetic patients the power increased in the theta band, in T5 (uncontrolled) and T5 and F7 (controlled). Conclusions: Diabetic patients without mild cognitive impairment show deficient intentional visuospatial learning which was worse in uncontrolled patients. Theta and gamma power increased in healthy participants during intentional learning principally in frontal areas. These EEG power changes were absent in diabetic patients. The reduced accuracy of diabetic patients in intentional visuospatial learning was associated with different EEG learning-related patterns.

Effects of acute high altitude hypoxia on EEG power in different emotional states

Objective: To investigate the effects of acute high altitude hypoxia on EEG power in different emotional states. Methods: This study was two-factor within-subject design (2 levels of oxygen environment ×4 levels of emotion type). Twelve male subjects aged between 20 and 25 years old were induced to produce four different types of emotions by emotional picture evoked paradigm: low valence and low arousal(LVLA), high valence and low arousal(HVLA), low valence and high arousal(LVHA), high valence and high arousal(HVHA). Brain Products 32 was used to collect EEG signals under different emotional states. The next day, a constant depressed oxygen chamber was used to simulate a 4 300 m plateau hypoxia environment, and the same group of subjects used the same experimental paradigm to collect EEG signals 10h after hypoxia. The collected EEG signals were analyzed by power spectrum (FFT), and the five frequency bands (Delta, Theta, Alpha, beta, gamma) of the frontal lobe (F3\Fz\F4) were analyzed by variance analysis of two-factor repeated measurements. Results: FFT analysis found that before and after acute hypoxia, the whole brain distribution of alpha wave in four emotional states was mainly concentrated in frontal and parietal leaves; the distribution of alpha wave in the whole brain was the least in relaxed emotional state. The results of the two-factor repeated measurement ANOVA showed that: ①the power of delta\ beta band was significantly affected by the oxygen environment(P＜0.05), and the power was enhanced under hypoxia. ②The power index of theta\ alpha band showed a significant interaction between the oxygen environment and emotional types(P＜0.05). Except for the HVLA emotional state, the power of theta alpha band was significantly enhanced under hypoxia. ③ The two factors had no significant influence on the gamma band(P＞0.05). Conclusion: Under the four kinds of emotional states, the difference of the influence of oxygen environment on brain activity was mainly in the frontal lobe, parietal lobe and part of temporal lobe. Of the four types of emotions, the oxygen environment had the least significant effect on brain activity in HVLA emotional states, while the rest showed significant differences.

Rhythm Violation Enhances Auditory-Evoked Responses to the Extent of Overriding Sensory Adaptation in Passive Listening.

Sensory systems utilize temporal structure in the environment to build expectations about the timing of forthcoming events. We investigated the effects of rhythm-based temporal expectation on auditory responses measured with EEG recorded from the frontocentral sites implicated in auditory processing. By manipulating temporal expectation and the interonset interval (IOI) of tones, we examined how neural responses adapted to auditory rhythm and reacted to stimuli that violated the rhythm. Participants passively listened to the tones while watching a silent nature video. In Experiment 1 (n = 22), in the long-IOI block, tones were frequently presented (80%) with 1.7-sec IOI and infrequently presented (20%) with 1.2-sec IOI, generating unexpectedly early tones that violated temporal expectation. Conversely, in the short-IOI block, tones were frequently presented with 1.2-sec IOI and infrequently presented with 1.7-sec IOI, generating late tones. We analyzed the tone-evoked N1-P2 amplitude of ERPs and intertrial phase clustering in the theta-alpha band. The results provided evidence of strong delay-dependent adaptation effects (short-term, sensitive to IOI), weak cumulative adaptation effects (long-term, driven by tone repetition over time), and robust temporal-expectation violation effects over and above the adaptation effects. Experiment 2 (n = 22) repeated Experiment 1 with shorter IOIs of 1.2 and 0.7 sec. Overall, we found evidence of strong delay-dependent adaptation effects, weak cumulative adaptation effects (which may most efficiently accumulate at the tone presentation rate of ∼1 Hz), and robust temporal-expectation violation effects that substantially boost auditory responses to the extent of overriding the delay-dependent adaptation effects likely through mechanisms involved in exogenous attention.

Neurophysiological, Oculomotor, and Computational Modeling of Impaired Reading Ability in Schizophrenia.

Schizophrenia (Sz) is associated with deficits in fluent reading ability that compromise functional outcomes. Here, we utilize a combined eye-tracking, neurophysiological, and computational modeling approach to analyze underlying visual and oculomotor processes. Subjects included 26 Sz patients (SzP) and 26 healthy controls. Eye-tracking and electroencephalography data were acquired continuously during the reading of passages from the Gray Oral Reading Tests reading battery, permitting between-group evaluation of both oculomotor activity and fixation-related potentials (FRP). Schizophrenia patients showed a marked increase in time required per word (d = 1.3, P < .0001), reflecting both a moderate increase in fixation duration (d = .7, P = .026) and a large increase in the total saccade number (d = 1.6, P < .0001). Simulation models that incorporated alterations in both lower-level visual and oculomotor function as well as higher-level lexical processing performed better than models that assumed either deficit-type alone. In neurophysiological analyses, amplitude of the fixation-related P1 potential (P1f) was significantly reduced in SzP (d = .66, P = .013), reflecting reduced phase reset of ongoing theta-alpha band activity (d = .74, P = .019). In turn, P1f deficits significantly predicted increased saccade number both across groups (P = .017) and within SzP alone (P = .042). Computational and neurophysiological methods provide increasingly important approaches for investigating sensory contributions to impaired cognition during naturalistic processing in Sz. Here, we demonstrate deficits in reading rate that reflect both sensory/oculomotor- and semantic-level impairments and that manifest, respectively, as alterations in saccade number and fixation duration. Impaired P1f generation reflects impaired fixation-related reset of ongoing brain rhythms and suggests inefficient information processing within the early visual system as a basis for oculomotor dyscontrol during fluent reading in Sz.

Differences in EEG patterns between tonic and high frequency spinal cord stimulation in chronic pain patients

ObjectiveTo investigate the differences in neural patterns between spinal cord stimulation (SCS) waveforms (60-Hz tonic vs 10-KHz high frequency stimulation, HFS) and their correlation to stimulation-induced pain relief. MethodsWe recorded 10-channel electroencephalogram (EEG) in response to stimulation ON and OFF in 9 chronic pain patients (4 women, 5 men) during SCS surgery and examined the intraoperative spatio-spectral EEG features. ResultsWe discovered stronger relative alpha power in the somatosensory region and higher trend in alpha/theta peak power ratio in frontal cortex with HFS. We also observed a shift in peak frequency from theta to alpha rhythms in HFS as compared to baseline and tonic stimulation, where slower theta activity was maintained. Further, a positive correlation was found between changes in Oswestry disability index (ODI) scores (from preoperative to postoperative) and HFS-induced alpha/theta peak power ratio in frontal and somatosensory regions. ConclusionsAltogether, our findings suggest that dynamic spectral interactions in theta-alpha band and their spatial distributions might be the first intraoperative neural signatures of pain relief induced by HFS in chronic pain. SignificanceExamining electrophysiological changes intraoperatively has a potential to elucidate response to SCS therapy prior to device selection, reducing the healthcare expenditures associated with failed implants.

A controlled clinical crossover trial of exercise training to improve cognition and neural communication in pediatric brain tumor survivors

ObjectiveTo assess the efficacy of aerobic exercise training to improve controlled attention, information processing speed and neural communication during increasing task load and rest in pediatric brain tumor survivors (PBTS) treated with cranial radiation. Methods: Participants completed visual-motor Go and Go/No-Go tasks during magnetoencephalography recording prior to and following the completion of 12-weeks of exercise training. Exercise-related changes in response accuracy and visual-motor latency were evaluated with Linear Mixed models. The Phase Lag Index (PLI) was used to estimate functional connectivity during task performance and rest. Changes in PLI values after exercise training were assessed using Partial Least Squares analysis. Results: Exercise training predicted sustained (12-weeks) improvement in response accuracy (p<0.05) during No-Go trials. Altered functional connectivity was detected in theta (4–7Hz) alpha (8–12Hz) and high gamma (60–100Hz) frequency bands (p<0.001) during Go and Go/No-Go trials. Significant changes in response latency and resting state connectivity were not detected. Conclusion: These findings support the efficacy of aerobic exercise to improve controlled attention and enhance functional mechanisms under increasing task load in participants. Significance: It may be possible to harness the beneficial effects of exercise as therapy to promote cognitive recovery and enhance brain function in PBTS.

Combined behavioral and electrophysiological evidence for a direct cortical effect of prefrontal tDCS on disorders of consciousness

Severe brain injuries can lead to long-lasting disorders of consciousness (DoC) such as vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS). While behavioral assessment remains the gold standard to determine conscious state, EEG has proven to be a promising complementary tool to monitor the effect of new therapeutics. Encouraging results have been obtained with invasive electrical stimulation of the brain, and recent studies identified transcranial direct current stimulation (tDCS) as an effective approach in randomized controlled trials. This non-invasive and inexpensive tool may turn out to be the preferred treatment option. However, its mechanisms of action and physiological effects on brain activity remain unclear and debated. Here, we stimulated 60 DoC patients with the anode placed over left-dorsolateral prefrontal cortex in a prospective open-label study. Clinical behavioral assessment improved in twelve patients (20%) and none deteriorated. This behavioral response after tDCS coincided with an enhancement of putative EEG markers of consciousness: in comparison with non-responders, responders showed increases of power and long-range cortico-cortical functional connectivity in the theta-alpha band, and a larger and more sustained P300 suggesting improved conscious access to auditory novelty. The EEG changes correlated with electric fields strengths in prefrontal cortices, and no correlation was found on the scalp. Taken together, this prospective intervention in a large cohort of DoC patients strengthens the validity of the proposed EEG signatures of consciousness, and is suggestive of a direct causal effect of tDCS on consciousness.

Cortico-subthalamic Coherence in a Patient With Dystonia Induced by Chorea-Acanthocytosis: A Case Report.

The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) treatment in Parkinson’s disease (PD) but much less frequently targeted for other disorders. Here we report the results of simultaneous local field potential (LFP) recordings and magnetoencephalography (MEG) in a single patient who was implanted bilaterally in the STN for the treatment of dystonia induced by chorea-acanthocytosis. Consistent with the previous results in PD, the dystonia patient showed significant subthalamo-cortical coherence in the high beta band (28–35 Hz) on both sides localized to the mesial sensorimotor areas. In addition, on the right side, significant coherence was found in the theta-alpha band (4–12 Hz) that localized to the medial prefrontal cortex with the peak in the anterior cingulate gyrus. Comparison of STN power spectra with a previously reported PD cohort showed increased power in the theta and alpha bands and decreased power in the low beta band in dystonia which is consistent with most of the previous studies. The present report extends the range of disorders for which cortico-subthalamic oscillatory connectivity has been characterized. Our results strengthen the evidence that at least some of the subthalamo-cortical oscillatory coherent networks are a feature of the healthy brain, although we do not rule out that coherence magnitude could be affected by disease.

A Continuous Clustering Algorithm for Detection of Local Sleep in Humans.

Research in animal models has shown that many EEG sleep features reflect local conditions, which is a consequence of relative inactivity of neuronal clusters. In humans, the authors previously reported that focal sleep patterns appear on the cortex during the wake state and suggested that this underlies the condition described as drowsiness. The focal changes at individual electrodes appeared as a combination of increased instantaneous amplitude in the delta band and decreased instantaneous frequency in the theta-alpha band during non-REM sleep, with the opposite occurring during the wake state, permitting their categorization as "active" and "inactive." A limitation of the previous work was the use of a binary k-means clustering algorithm, which created the possibility that the findings were biased toward a predominantly inactive state while the study subject was still awake. The present study tested the hypothesis that analyzing the same data by using a continuous rather than binary classifier would overcome this limitation. An analysis was performed on records from six patients with refractory epilepsy who were undergoing video-electrocorticographic monitoring with implanted subdural grid electrodes. A fuzzy c-means clustering algorithm was utilized after feature extraction from the recordings to create state classifications for each moment in each recording. A subsequent analysis was performed to determine the relative contributions of instantaneous amplitude versus instantaneous frequency to the classification. Localized state changes consistent with the hypothesis were observed. The contributions from instantaneous frequency and amplitude appeared roughly equal. This study reveals evidence of local sleep during the wake state in humans.

Dynamic Causal Modeling of the Relationship between Cognition and Theta-alpha Oscillations in Adults with Down Syndrome.

Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta–alpha activity (4–13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann’s Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta–alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4–13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.

Cross-frequency network analysis of functional brain connectivity in temporal lobe epilepsy**Project supported by the National Natural Science Foundation of China (Grant No. 61302002).

In this study, we investigate the cross-frequency coupling and functional brain networks in the subjects with temporal lobe epilepsy (TLE) using interictal EEG signals. The phase to phase synchronization within and across frequency bands is calculated and a significant difference between the epilepsy and control groups is observed. Compared with the controls, the epilepsy patients exhibit a stronger within-frequency coupling (WFC) within theta and beta bands, and shows a stronger cross-frequency coupling (CFC) in the delta–alpha and theta–alpha band pairs, but a weakened CFC in alpha–beta band pairs. The weakened coupling between alpha and high frequency band reflects a suppression of phase modulation between the brain regions related to epilepsy. Moreover, WFC and CFC are positively correlated, which is higher in the patients relative to controls. We further reconstruct functional brain connectivity and find that both WFC and CFC networks show small-world properties. For the epilepsy, the small-world efficiency is enhanced in the CFC networks in delta–alpha and theta–alpha band pairs, whereas weakened between alpha and beta bands, which suggests a shift away from the optimal operating point in the epileptic brain with a new balance between WFC and CFC. Our results may help us to understand the important role of information communication across different frequency bands and shed new light on the study of pathology of epilepsy.

Working memory performance in the elderly relates to theta-alpha oscillations and is predicted by parahippocampal and striatal integrity

The ability to maintain information for a short period of time (i.e. working memory, WM) tends to decrease across the life span with large inter-individual variability; the underlying neuronal bases, however, remain unclear. To address this issue, we used a multimodal imaging approach (voxel-based morphometry, diffusion-tensor imaging, electroencephalography) to test the contribution of brain structures and neural oscillations in an elderly population. Thirty-one healthy elderly participants performed a change-detection task with different load conditions. As expected, accuracy decreased with increasing WM load, reflected by power modulations in the theta-alpha band (5–12 Hz). Importantly, these power changes were directly related to the tract strength between parahippocampus and parietal cortex. Furthermore, between-subject variance in gray matter volume of the parahippocampus and dorsal striatum predicted WM accuracy. Together, our findings provide new evidence that WM performance critically depends on parahippocampal and striatal integrity, while theta-alpha oscillations may provide a mechanism to bind the nodes within the WM network.

Delirium is associated with frequency band specific dysconnectivity in intrinsic connectivity networks: preliminary evidence from a large retrospective pilot case-control study

BackgroundPathophysiological concepts in delirium are not sufficient to define objective biomarkers suited to improve clinical approaches. Advances in neuroimaging have revalued electroencephalography (EEG) as a tool to assess oscillatory network activity in neuropsychiatric disease. Yet, research in the field is limited to small populations and largely confined to postoperative delirium, which impedes generalizability of findings and planning of prospective studies in other populations. This study aimed to assess effect sizes of connectivity measures in a large mixed population to demonstrate that there are measurable EEG differences between delirium and control patients.MethodsThis retrospective pilot study investigated EEG measures as biomarkers in delirium using a case-control design including patients diagnosed with delirium (DSM-5 criteria) and age-/gender-matched controls drawn from a database of 9980 patients (n = 129 and 414, respectively). Assessors were not blinded for groups. Power spectra and connectivity estimates, using the weighted phase log index, of continuous EEG data were compared between conditions. Alterations of information flow through nodes of intrinsic connectivity networks (ICN; default mode, salience, and executive control network) were evaluated in source space using betweenness centrality. This was done frequency specific and network nodes were defined by the multimodal human cerebral cortex parcellation based on human connectome project data.ResultsDelirium and control patients exhibited distinct EEG power, connectivity, and network characteristics (F(72,540) = 70.3, p < .001; F(493,1079) = 2.69, p < .001; and F(718,2159) = 1.14, p = .007, respectively). Connectivity analyses revealed global alpha and regional beta band disconnectivity that was accompanied by theta band hyperconnectivity in delirious patients. Source and network analyses yielded that these changes are not specific to single intrinsic connectivity networks but affect multiple nodes of networks engaged in level of consciousness, attention, working memory, executive control, and salience detection. Effect sizes were medium to strong in this mixed population of delirious patients.ConclusionsWe quantified effect sizes for EEG connectivity and network analyses to be expected in delirium. This study implicates that theta band hyperconnectivity and alpha band disconnectivity may be essential mechanisms in the pathophysiology of delirium. Upcoming prospective studies will build upon these results and evaluate the clinical utility of identified EEG measures as therapeutic and prognostic biomarkers.

Occipital EEG Activity for the Detection of Nocturnal Hypoglycemia.

Nocturnal hypoglycemia is dangerous that threatens patients because of its unclear symptoms during sleep. This paper is a study of hypoglycemia from 8 patients with type 1 diabetes (T1D) at night. O1 and O2 EEG data of the occipital lobe associated with glycemic episodes were analyzed. Frequency features were computed from Power Spectral Density using Welch's method. Centroid alpha frequency reduced significantly ($\mathrm{P}\lt 0.0001$) while centroid theta increased considerably ($\mathrm{P}\lt 0.01$). Spectral entropy of the unified theta-alpha band rose significantly ($\mathrm{P}\lt 0.005$). These occipital features acted as the input of a Bayesian regularized neural network for detecting hypoglycemic episodes. The classification results were 73% and 60% of sensitivity and specificity, respectively.

Hypoglycemia-Associated EEG Changes Following Antecedent Hypoglycemia in Type 1 Diabetes Mellitus.

Recurrent hypoglycemia has been shown to blunt hypoglycemia symptom scores and counterregulatory hormonal responses during subsequent hypoglycemia. We therefore studied whether hypoglycemia-associated electroencephalogram (EEG) changes are affected by an antecedent episode of hypoglycemia. Twenty-four patients with type 1 diabetes mellitus (10 with normal hypoglycemia awareness, 14 with hypoglycemia unawareness) were studied on 2 consecutive days by hyperinsulinemic glucose clamp at hypoglycemia (2.0-2.5 mmol/L) during a 1-h period. EEG was recorded, cognitive function assessed, and hypoglycemia symptom scores and counterregulatory hormonal responses were obtained. Twenty-one patients completed the study. Hypoglycemia-associated EEG changes were identified on both days with no differences in power or frequency distribution in the theta, alpha, or the combined theta-alpha band during hypoglycemia on the 2 days. Similar degree of cognitive dysfunction was also present during hypoglycemia on both days. When comparing the aware and unaware group, there were no differences in the hypoglycemia-associated EEG changes. There were very subtle differences in cognitive function between the two groups on day 2. The symptom response was higher in the aware group on both days, while only subtle differences were seen in the counterregulatory hormonal response. Antecedent hypoglycemia does not affect hypoglycemia-associated EEG changes in patients with type 1 diabetes mellitus.

Focal Changes to Human Electrocorticography With Drowsiness: A Novel Measure of Local Sleep.

Drowsiness may be defined as the progressive loss of cortical processing efficiency that occurs with time passing while awake. This loss of cortical processing efficiency is reflected in focal changes to the electroencephalogram, including islands of increased delta power concurrent with drop-offs in neuronal activity (i.e., focal cortical inactivity). The authors hypothesized that these focal changes are evidenced at individual electrodes by combination of increased instantaneous amplitude in delta band and decreased instantaneous frequency in theta-alpha band, permitting their categorization as "active" and "inactive." An analysis of records from six patients with refractory epilepsy undergoing video-electrocorticographic monitoring was conducted. Feature extraction and state classification on multiple recordings revealed focal changes consistent with the hypothesis, as well as progressively increased numbers of inactive electrodes with time awake. The implications of these findings on the study of sleep, and particularly local sleep, are discussed.